Maximize Similarity
Reported by candidates from Amazon's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
You're prepping for Amazon's October OA and hit Maximize Similarity. No problem statement leaked yet, but the title alone tells you this is about finding some optimal pairing or arrangement that minimizes difference. Amazon loves these medium-difficulty greedy or sorting plays, and they're testing whether you can spot the trade-off. StealthCoder sits invisible on your screen during the live OA, reading the exact prompt and ready to feed you the pattern if you freeze up. You've got 24-72 hours, so lock down the core approach now.
Pattern and pitfall
Maximize Similarity typically means pairing elements to minimize total distance or difference. The pattern is usually sorting first, then greedy pairing. Sort the array, then pair adjacent elements (or elements at symmetric positions), and sum the absolute differences. The trick is recognizing that after sorting, the optimal pairing becomes obvious: consecutive elements yield the smallest gaps. Watch for edge cases: odd-length arrays, negative numbers, whether you're pairing or just selecting a subset. Common pitfall is trying to match elements greedily without sorting, which wastes time. During your live OA, if the exact rules blur, StealthCoder reads the screen and confirms whether you're pairing, selecting, or rearranging. That clarity prevents you from coding the wrong solution.
If this hits your live OA and you blank, StealthCoder solves it in seconds, invisible to the proctor.
You can drill Maximize Similarity cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it.
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Amazon reuses patterns across OAs. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Maximize Similarity FAQ
Is this a sorting plus greedy problem?+
Most likely. Sort the array first. Then pair or select greedily based on minimizing the sum of differences. Once sorted, the locally optimal choice (adjacent pairs) is globally optimal. Test this hypothesis against the full problem statement when you see it.
What if the problem involves rearranging two arrays?+
Sort both arrays, then pair them element-by-element in the same order. This minimizes the sum of absolute differences between paired elements. It's a classic two-array greedy pattern Amazon revisits often.
How do I handle negative numbers or a mix of signs?+
Sorting still works. After sorting, the greedy pairing rule holds regardless of sign. The goal is to match values close to each other, and sorting ensures that. Don't overthink the sign until you see the actual prompt.
Can I solve this in 20 minutes cold?+
If you recognize the sort-and-pair pattern, yes. The implementation is straightforward once the insight clicks. The risk is blank panic if you don't see the pattern on first read. That's where your hedge kicks in.
Should I expect a DP or greedy approach here?+
Greedy is more likely given the title. DP Maximize Similarity problems exist but are rarer. Assume greedy first. If that doesn't fit after reading the full prompt, revisit the state-space and memo table.